On the island of Madagascar, off the southeast coast of Africa, NASA-funded biologist Christopher Raxworthy has stalked chameleons for the last 20 years. The most remote research camps can require nine days of bug-ridden hiking, hauling food and supplies. Most of his surveys for lizards are done at night, when chameleons sleep, and their skins turn grayish, making the hunt easier.

One big challenge for biologists like Raxworthy is that nobody knows for certain what species exist in remote areas of the tropics, and even pinpointing the best places to look for specific creatures or plants is tricky. Madagascar, for instance, is one of 25 “hotspots” around the world. Combined, these sites account for only 1.4 percent of the planet’s land area, and yet contain 44 percent of all plant species and 35 percent of all land vertebrate species. That’s a lot of diversity packed into a pretty small space, and with humans changing Earth’s land cover so rapidly, conservationists often struggle to identify biologically rich areas to protect before they are lost forever.

Chameleons, native to the isolated island of Madagascar, are just one of the many animal and plant species that scientists are now studying with satellites. With remote sensing data, researchers are able to accurately map species’ habitats and plan conservation programs. (Photograph copyright David R. Parks, Madagascar Biodiversity and Conservation, Missouri Botanical Garden)

Some scientists are using remote-sensing technology to better understand relationships between species and the places they live. Satellites’ ability to routinely observe even the most remote areas can make biologists’ search for important species and habitats quicker and easier.

Raxworthy, an associate curator with the American Museum of Natural History, New York, combines vast amounts of environmental information on Madagascar collected by satellites with records from museum collections that identify areas where lizards have previously been found. He feeds these data into computer models, which spit out maps showing the most likely locales for chameleons.

“The most fundamental payoffs from new technologies such as satellite data are in the remote areas of the tropics,” Raxworthy says. “We can very quickly get a picture of where species might be distributed. If one were to send out survey teams alone, it might take thousands of years to generate the level of information that satellites provide.”

New Tools

As biologists, ecologists, and conservationists are under pressure to understand why and where species are being lost, satellites offer certain advantages. They regularly see vast areas of the Earth all at once, making comparisons over time possible. Also, satellites provide access to remote areas of the world, where gathering comprehensive, routinely updated data on the ground can be nearly impossible. For example, NASA’s Earth Observing System series of satellites includes satellites that monitor everything from how much of the natural landscape humans clear each year for farmland or urban growth, to the frequency and severity of air pollution events, to increased ocean temperatures in sensitive coral habitat.

Along with other agencies, NASA is entering “a new age of remote sensing,” says Woody Turner, a program scientist at NASA’s Office of Earth Science. In 2003, Turner was the lead author of an article published in the scientific journal Trends in Ecology & Evolution (TREE). He and his co-authors outlined the current uses of remote sensing in biodiversity science and conservation. “We are starting to get from space a lot of parameters [characteristics about Earth] that people historically felt were important but didn’t have access to,” Turner adds.

In the past, satellites have enabled researchers to see the Earth on large scales, but more recently, they provide information on smaller scales, too. In some rare cases, high resolution satellites can directly observe species on the ground. Mostly though, environmental data or images from satellites offer indirect but invaluable information about species and their habitat. Raxworthy’s experiment with chameleon habitat in Madagascar showed that satellites used in tandem with computer models allow researchers to predict the best remaining areas to protect.

“Using satellite imagery is an extremely compelling way to show politicians and land managers what is going on and how land has changed,” says Ned Gardiner, one of Turner’s co-authors and a geographer and ecologist at the American Museum of Natural History in New York.

“One of the most important global changes today is the decline of biodiversity,” emphasizes Turner. “It behooves us to understand what we are doing.” While data from satellites are publicly available, Turner feels that ecologists and others have been somewhat slow to catch on and start using them for conservation-related studies.

Twenty-five locations around the world are characterized as “biodiversity hotpsots” by Conservation International. Often remote, these areas hold 44 percent of all plant species and 35 percent of all land vertebrate species in only 1.4 percent of the Earth’s landmass. (Map by Robert Simmon)

Different Ways of Seeing Species

There are several ways space-based technologies can help us understand where species live and why they live there. One way is to directly observe species using satellite sensors with spatial resolutions high enough to actually discern individuals, like a tree or a whale, or collections of species, like a grove of trees. Also, Global Positioning System (GPS) devices allow scientists to track animals’ movements in real time. Difficulties with directly sensing species include the relatively small size of most species, the limitations of the technologies, clouds or vegetation getting in the way, and cost.

Because of those limitations, indirect sensing currently provides more opportunities for biologists. Indirectly, scientists can study species by gathering information about their habitats. Satellite remote sensors provide important environmental, biological, and physical information—topography, rainfall, forest cover—that reveal where species are likely to be found.

Direct Sensing

Observing Animals

Most satellites provide images in lower spatial resolutions (level of detail) that lack the power to detect an individual tree or animal. Still, recent advancements have made direct remote sensing of certain individuals increasingly feasible. For example, a few commercial satellites are now capable of spatial resolutions of one meter or less. At least one has a resolution of 60 centimeters. This means the smallest unit of data captured, called a pixel, averages information over an area of 60 square centimeters, an area of the Earth’s surface roughly 2 feet by 2 feet.

“The conventional wisdom is that you need five to ten pixels on a target to recognize it for what it is,” said Ron Abileah, a staff scientist at Vista Research Inc., a company that does commercial and defense research and development. Abileah has researched the possibility of applying imagery from the commercial satellite IKONOS to find and count whales at or near the ocean surface. Space Imaging’s IKONOS satellite produces color images at 4-meter resolution. Abileah’s preliminary studies suggest that this resolution shows some promise, and might one day provide another tool for people who monitor these and other protected whale species.

Observing Plants

Some plants make themselves an easy target for satellite sensors by growing in dense mats that spread over many square miles. Satellites that see surface details have been used to map the spread of non-native freshwater plant species, like the water hyacinth invasion in East Africa’s Lake Victoria and the Rio Grande in the southern United States, and the duckweed invasion of Lake Maracaibo in northern South America.

Another way to use satellites to directly track plant species is through new hyperspectral sensors, such as NASA’s Hyperion instrument aboard the Earth Observing-1 (EO-1) satellite, which detects 220 distinct wavelengths of light reflected from the Earth. Each surface, whether it is a rock or a maple leaf, reflects its own unique spectrum of light. By detecting the distinct wavelengths of light that represent the signature of a certain type of organism, species community, or material, scientists can directly distinguish different types of surfaces—vegetation from water, soybeans from corn, or pine trees from oaks.

Hyperspectral technologies have come in handy in detecting and mapping invasive species that threaten to take over an area. Studies done in the Theodore Roosevelt National Park in Western North Dakota demonstrated that hyperspectral instruments could detect infestations of leafy spurge, an aggressive, persistent, deep-rooted perennial, which grows to a height of 1 meter (3 ft.) or taller. The white-sapped plant has infested more than five million acres of land in 35 U.S. states and the prairie provinces of Canada, overrunning native plants.

Scientists used three hyperspectral sensors at three separate spatial resolutions to detect the invasive plant. NASA’s Hyperion instrument had the best results and accurately detected and mapped leafy spurge up to 80 percent of the time. In separate studies, Landsat has also been used to detect leafy spurge in states throughout the Western United States. By identifying areas of greatest concern with satellites, land managers can save time and money by focusing their resources on surveying specific areas.

Indirect Sensing

When direct sensing is not possible, satellites provide detailed information about habitats at large scales. As scientists learn more about where certain species live and why they live in those places, they can apply environmental and topographical information gained from satellites to understand the needs of these organisms and where else they are likely to be found.

Modeling Watershed Processes

Remote sensing may never be good at detecting what lives in a stream, but moderate-resolution satellite data can provide sufficient detail over a wide enough area to model and analyze watershed processes. Ned Gardiner uses remote-sensing data to model how stream ecosystems respond to watershed disturbances. In one study, he used Landsat satellite data of land cover and United States Geological Survey (USGS) topographical data of a mountainous area in North Carolina to determine that sediment eroding into highland streams from disturbed land was allowing species that are widely distributed in larger rivers with more fine sediment to invade highland streams. When sediment supply becomes excessive, these widely distributed, sediment-tolerant species replace highland endemics—fish species that are found only in small, steep, clear-water streams. As an added benefit to land use planners, Gardiner also found that the length of unimproved roads in a watershed is a very good predictor of the sediment load of streams and rivers in the watershed.

This kind of watershed modeling will continue to evolve as ecologists gain more access to detailed data. “Just as different vegetation types have distinct signatures, watersheds have land use signatures that indicate ecological health of the streams they support,” says Gardiner. Watershed models that use satellite-based observations of the land surface may give people insights into how a planned land use, such as a shopping development or a logging road—might change local ecosystems and organisms.

Predicting Species Habitat

While no single environmental factor drives patterns of biodiversity, many researchers believe three factors play roughly equal roles: vegetation growth, habitat structure, and climate. In 1998, Oxford University zoologists demonstrated how satellite-derived information on environmental conditions could be used to identify habitats of bird species unique (endemic) to certain regions in East Africa.

The scientists used a satellite-based indicator of vegetation called “NDVI,” short for Normalized Difference Vegetation Index, a measure of vegetation greenness. The greenness is an indication of vegetation abundance and health in an ecosystem. The scientists also used estimates of rainfall based on data collected by the Meteosat series of geostationary satellites. By combining these satellite observations of modern environmental conditions with elevation data, the scientists predicted the endemic birds’ habitats 89 percent of the time.

Mapping Forests in 3-D

Most satellite sensors passively record light and heat reflected or emitted toward them from Earth, creating a flat image of the Earth’s surface below. New active sensors, such as lidar, can record information in three dimensions, making it possible to measure habitat structure, topography, and biomass. Active sensors emit a pulse of electromagnetic energy, such as radio waves or light, toward an object and then measure the energy that bounces back to a detector and the time interval between sending and receiving it. In forests, lidar sensors use the return signals to detect the height of the canopy top, ground elevation, and the positions of leaves and branches in between. Longer wavelength pulses of radars can penetrate clouds, and the longest radar wavelengths can penetrate tree canopies, or in cases of bare, dry soil, even the surface of the Earth to depths of a meter or more.

The ability to penetrate forest canopies and clouds means lidar and radar could be important tools for measuring biomass and for mapping vegetation structure in three dimensions. Knowing the 3-D vegetation structure in an ecosystem is important for determining how many different species might live there. As Gardiner points out, if a researcher wants to survey spiders in his or her local area, more varieties will be found near a stream with a structurally diverse forest containing several “habitats” or levels, as opposed to a stream area without a forest nearby. Active sensors are providing detailed views of forest structures that have never been possible before.

Very high resolution satellites are capable of directly observing some animals. Using data from the Ikonos satellite Ron Abileah detected humpack whales off the coast of Maui. The light grey objects on the left of this image are likely a humpback whale mother and her calf. To the right is a whale-watching boat. (Images courtesy Ron Abileah, based on data copyright Space Imaging.)

Ralph Dubayah, a professor of geography at the University of Maryland, College Park, has used the Laser Vegetation Imaging Sensor (LVIS), an aircraft-mounted lidar sensor, and owl demographic data to analyze nesting habitat of spotted owls in the Sierra Nevada Mountains. He wanted to see if there were any structural differences between the places in the forest where the owls nested or traveled and the places where they did not.

Dubayah’s team mapped areas with spotted owl nests, followed the owls’ movements, and drew a circle around their domain. Using LVIS, the researchers then analyzed the forest structure within and around the owls’ range. LVIS provided data on canopy structure, the amount of light filtering through the leaves down to the ground, and the height of trees. “We found a pretty strong relationship between these forest structures and owl nesting patterns,” Dubayah says. In other words, for owls’ nests, not just any area will do.

How does knowing the owl’s structural preference help foresters and conservationists? The forests of the Sierra Nevada Mountains are subject to tree-thinning efforts to reduce wood fuel for fires, creating controversy. Loggers and fire prevention specialists want to remove the wood, while environmentalists and conservationists seek to protect owl habitat. By quantifying the levels of biomass, canopy structure, and light that owls prefer, people can now know exactly how much of the forest may be removed before such practices impinge upon the owls’ habitat.

“In the absence of this kind of quantitative analysis, there is no way to know how much we can thin,” Dubayah said. “Lidar provides this quantitative underpinning that has been missing. Vertical profiles, distribution of trees, tree heights, these are exceptionally difficult data to get on the ground, whereas lidar explicitly gives you the vertical structure you are looking for.”

New remote sensing technologies are mapping ecosystems in new ways. Data from air- and spaceborne lasers reveal forest canopies in three-dimensions. This image shows the structure of a tropical forest in La Selva, Costa Rica. Color corresponds to the amount of laser energy reflected from trees and leaves back to an airborne sensor—a measurement proportional to the density of the forest canopy. (Image courtesy John Weishampel, University of Central Florida)

Pros and Cons

There is no question that satellites and computer models are opening the door to new ways of looking at ecological issues. While these new technologies and techniques offer a far greater range of information than has ever been possible before, there are still challenges to using satellite data effectively. For starters, remote sensing data need to be validated, or compared with other sources of information to see if there is agreement. Without proper validation, satellite data should not be taken at face value. Such ‘ground-truth’ information might come from ground-based sensors, higher-resolution remote-sensing sources, like aerial photographs, or researchers in the field.

“You still need to put effort into ground-truthing,” says Raxworthy. “You just can’t look at images from space and use computers to give you the answers. You still have to have a muddy-boots biologist trudging through the forests.”

Another consideration is the cost for imagery. As satellites and computers become more sophisticated, the costs are going down. Raxworthy recalls when he first started as a biodiversity researcher, the price of satellite imagery was beyond his meager budget. “In the mid-1980s, I would have given my eye-teeth to get satellite images of Madagascar,” he says. “Now I can download MODIS [NASA’s Moderate Resolution Imaging Spectroradiometer] images for free.”

In general, imagery from the newer and higher-spatial-resolution satellites is more expensive than lower-resolution imagery. Anyone can now buy a specialized image from the Landsat 7 satellite, currently run by the USGS, which offers 15-meter-resolution black-and-white images and 30-meter color images. These cost about 600 dollars per scene, down from the thousands of dollars for images from previous Landsat satellites. Handling satellite images requires special computer software and hardware tools, and while they are not negligible, these computing costs are declining.

Along with getting access to images and computers to process images, the next generation of researchers will need training to use these new tools. “It still takes a certain amount of knowledge to do this,” says Turner. Although many types of remote sensing data are in the research phase of development and currently are beyond the capabilities of most researchers, Turner says, “The article in TREE was a call to say, ‘Hey, think about this.’ This is especially true for the people who are just coming up in schools.”

The Future

In their overview article in TREE, Turner and colleagues point out that a perception problem exists within science communities that would benefit from these new tools. Though technology has advanced, contends Turner, many researchers cling to old standards, back in the days when satellites recorded data at spatial scales that were too coarse to be relevant to the needs of ecologists and evolutionary and conservation biologists. “Perception may be more the problem now than technology,” he says.

“It cuts both ways,” says Turner, describing how scientists in the field view remote-sensing technology. “On the one hand, people can be naïve and think it’s an eye in the sky, and we can zoom in and see all the elephants and count them.” On the other hand, some researchers do not recognize how realistic and applicable to their work these technologies might be. “There’s no question that improvements have happened in the last 15 years,” says Turner, but in trying to educate people about the new technologies, “we don’t want to oversell this thing.”

Although remote sensing data are exceptional for exploring isolated areas, the information must be verified. Chris Raxworthy’s team discovered several new chameleon species while validating computer models of species’ ranges that they developed with the aid of satellite data. (Photograph copyright Chris Raxworthy)

Chameleon-hunter Raxworthy believes that in the future, as satellite data span greater area and longer time periods, coverage will become more diverse, and computer models will improve. He envisions a world where interactive programs will allow ecologists and biologists to choose any species they are working with, in any country, and simply input longitudes and latitudes into an interface. The computer would be able to spit out a model of distributions for that species, allowing researchers to ask ecological and evolutionary questions and get answers.

But today, the most pressing applications concern conservation issues. “Fifty years from now, the next generation of biologists will inherit a very different landscape than what we see right now. We’re the key generation, right now, to make the smartest decisions in terms of forest survival,” says Raxworthy.

“Time is our enemy, in this regard,” says Turner about biodiversity loss. “What is needed is more collaboration now among remote-sensing researchers and those working in biodiversity science and conservation. The tools are there. Let us hope the users will soon follow.”

Conference on Biological Fingerprinting: Using Remote Sensing for Improved Modeling and Monitoring of Biodiversity, December 3-5, 2001, People Center of the American Museum of Natural History, New York, NY.

Satellite data is usually unable to detect individual animals, but some extremely large individuals are visible from space. Conservationists in Amboseli National Park, Kenya, use data from the Quickbird satellite to track the movement of elephant herds, which appear in the left side of this image as bright ovals edged with dark shadows. (Images courtesy Amboseli Elephant Research Project, based on data copyright DigitalGlobe.)